The ethics of forgetting in an age of pervasive computing

In this paper, we examine the potential of pervasive computing to create widespread sousveillance, that will complement surveillance, through the development of lifelogs; socio-spatial archives that document every action, every event, every conversation, and every material expression of an individual’s life. Examining lifelog projects and artistic critiques of sousveillance we detail the projected mechanics of life-logging and explore their potential implications. We suggest, given that lifelogs have the potential to convert exterior generated oligopticons to an interior panopticon, that an ethics of forgetting needs to be developed and built into the development of life-logging technologies. Rather than seeing forgetting as a weakness or a fallibility we argue that it is an emancipatory process that will free pervasive computing from burdensome and pernicious disciplinary effects

Space time pixels

This paper reports the design of a networked system, the aim of which is to provide an intermediate virtual space that will establish a connection and support interaction between multiple participants in two distant physical spaces. The intention of the project is to explore the potential of the digital space to generate original social relationships between people that their current (spatial or social) position can difficultly allow the establishment of innovative connections. Furthermore, to explore if digital space can sustain, in time, low-level connections like these, by balancing between the two contradicting needs of communication and anonymity. The generated intermediate digital space is a dynamic reactive environment where time and space information of two physical places is superimposed to create a complex common ground where interaction can take place. It is a system that provides awareness of activity in a distant space through an abstract mutable virtual environment, which can be perceived in several different ways – varying from a simple dynamic background image to a common public space in the junction of two private spaces or to a fully opened window to the other space – according to the participants will. The thesis is that the creation of an intermediary environment that operates as an activity abstraction filter between several users, and selectively communicates information, could give significance to the ambient data that people unconsciously transmit to others when co-existing. It can therefore generate a new layer of connections and original interactivity patterns; in contrary to a straight-forward direct real video and sound system, that although it is functionally more feasible, it preserves the existing social constraints that limit interaction into predefined patterns

User-interface to a CCTV video search system

The proliferation of CCTV surveillance systems creates a problem of how to effectively navigate and search the resulting video archive, in a variety of security scenarios. We are concerned here with a situation where a searcher must locate all occurrences of a given person or object within a specified timeframe and with constraints on which camera(s) footage is valid to search. Conventional approaches based on browsing time/camera based combinations are inadequate. We advocate using automatically detected video objects as a basis for search, linking and browsing. In this paper we present a system under development based on users interacting with detected video objects. We outline the suite of technologies needed to achieve such a system and for each we describe where we are in terms of realizing those technologies. We also present a system interface to this system, designed with user needs and user tasks in mind

The concepts of surveillance and sousveillance: A critical analysis

The concept of surveillance has recently been complemented by the concept of sousveillance. Neither term, however, has been rigorously defined, and it is particularly unclear how to understand and delimit sousveillance. This article sketches a generic definition of surveillance and proceeds to explore various ways in which we might define sousveillance, including power differentials, surreptitiousness, control, reciprocity, and moral valence. It argues that for each of these ways of defining it, sousveillance either fails to be distinct from surveillance or to provide a generally useful concept. As such, the article concludes that academics should avoid the neologism, and simply clarify what sense of surveillance is at stake when necessary

CVABS: Moving Object Segmentation with Common Vector Approach for Videos

Background modelling is a fundamental step for several real-time computer vision applications that requires security systems and monitoring. An accurate background model helps detecting activity of moving objects in the video. In this work, we have developed a new subspace based background modelling algorithm using the concept of Common Vector Approach with Gram-Schmidt orthogonalization. Once the background model that involves the common characteristic of different views corresponding to the same scene is acquired, a smart foreground detection and background updating procedure is applied based on dynamic control parameters. A variety of experiments is conducted on different problem types related to dynamic backgrounds. Several types of metrics are utilized as objective measures and the obtained visual results are judged subjectively. It was observed that the proposed method stands successfully for all problem types reported on CDNet2014 dataset by updating the background frames with a self-learning feedback mechanism.Comment: 12 Pages, 4 Figures, 1 Tabl

Better Foreground Segmentation Through Graph Cuts

For many tracking and surveillance applications, background subtraction provides an effective means of segmenting objects moving in front of a static background. Researchers have traditionally used combinations of morphological operations to remove the noise inherent in the background-subtracted result. Such techniques can effectively isolate foreground objects, but tend to lose fidelity around the borders of the segmentation, especially for noisy input. This paper explores the use of a minimum graph cut algorithm to segment the foreground, resulting in qualitatively and quantitiatively cleaner segmentations. Experiments on both artificial and real data show that the graph-based method reduces the error around segmented foreground objects. A MATLAB code implementation is available at http://www.cs.smith.edu/~nhowe/research/code/#fgsegComment: 8 pages, 110 figures. Revision: Added web link to downloadable Matlab implementatio